Insu Paek, Ki Cole

Using R for Item Response Theory Model Applications

• Gebundenes Buch

Produktbeschreibung

This book introduces basic concepts of IRT and detailed information on how to use R IRT programs for IRT applications.

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Produktdetails

• Verlag: Routledge
• Seitenzahl: 282
• Erscheinungstermin: 10. September 2019
• Englisch
• Abmessung: 240mm x 161mm x 20mm
• Gewicht: 590g
• ISBN-13: 9781138542785
• ISBN-10: 1138542784
• Artikelnr.: 57732136

Autorenporträt

Insu Paek is an associate professor at Florida State University. Before he came to Florida State University, he worked as a psychometrician for large-scale assessment programs and in testing companies for several years. His research interests are educational and psychological measurement and item response modeling and its application. Ki Cole is an assistant professor at Oklahoma State University. She teaches graduate level educational statistics courses, including item response theory and factor analysis for the behavioural sciences. Her research interests include the theory and applications of psychometrics, scale development, understanding response tendencies, and software evaluation.

Inhaltsangabe

Preface
1. Introduction
2. Unidimensional IRT with Dichotomous Item Responses
3. Unidimensional IRT with Polytomous Item Responses
4. Unidimensional IRT for Other Applications
5. Multidimensional IRT for Simple Structure
6. Multidimensional IRT for Bifactor Structure
7. Limitations and Caveat

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Preface

1. Introduction

2. Unidimensional IRT with Dichotomous Item Responses

3. Unidimensional IRT with Polytomous Item Responses

4. Unidimensional IRT for Other Applications

5. Multidimensional IRT for Simple Structure

6. Multidimensional IRT for Bifactor Structure

7. Limitations and Caveat

Rezensionen

This book is a great introduction to both the R program for item response theory (IRT) analysis and IRT modeling itself for readers who want a firm grasp on both skills. This book is a helpful manual for understanding IRT concepts and background concisely and for easily learning the freely accessible R programs for doing IRT analyses. Reading this book is like catching two birds with one stone. This book is clearly written and amazingly easy to follow from installing the R program and executing the R command to interpreting the executed results. This book also provides practical advice, guidance, and specific details on utilizing the R program for practitioners, researchers, and graduate students in an introductory or an intermediate IRT course. The authors explain the essential background of various IRT models and the logic of each model in terms of practical applications. A major strength of the book is its consistent use of detailed examples to illustrate the concepts, the practical applications of IRT, and the thorough explanation of results for the executed examples. Another strong point is the general approachability and clarity of the text. Both practical users of IRT and beginners of the R program will benefit from this clear text and detailed examples. As a practitioner who frequently uses IRT but has little experience with R for IRT analysis, I strongly recommend this book as a learning tool for both IRT and R IRT programs.

Dr. Hyeonjoo Oh, Senior psychometrician, Educational Testing Service